This invention relates to imaging systems, and in particular to a display processor that enhances the simultaneous display of multiple types of resolution in such systems.
Ultrasound images are used diagnostically for two different purposes: the display of structural details of tissue, and the differentiation of different types of tissue. A high spatial resolution (or detail resolution) in the image maximizes the ability of the user to detect fine structural details. A high contrast resolution in the image maximizes the user's ability to detect tissue type differences.
One of the fundamental limitations on contrast resolution is speckle noise. Speckle noise is inherent to coherent imaging systems and is caused by coherent (phase-sensitive) interference of waves scattered by structures too fine to be resolved. Speckle noise does not carry information on the structural details of the object, but its low frequency components carry information on the mean backscattering strength of the object. For this reason, high frequency components of speckle noise should be reduced in order to improve contrast resolution.
Various signal processing techniques have been used to improve contrast resolution. Low-pass video filters, low-pass scan conversion filters, and even the limited bandwidth of the display monitor can be used to reduce high-frequency spatial variations of speckle noise. In this way, differences in mean backscattering strength from one tissue to another can be significantly accentuated. The spatial smoothing associated with this approach to improving contrast resolution significantly reduces detail resolution.
Bamber U.S. Pat. No. 4,783,839 discloses a system for reducing speckle noise that varies the amount of smoothing across the image as a function of how closely individual regions of the image resemble speckle. In many cases speckle noise is superimposed on resolvable structural details of the object, and diagnostically useful detail resolution therefore can be lost.
Non-linear display mapping is another signal processing technique that has been used to improve contrast resolution. Especially when cascaded with smoothing video filters, non-linear display maps can increase contrast resolution at selected display intensity levels at the expense of reduced detail and contrast resolution at all other display intensity levels.
Speckle noise can also be reduced during image formation by any of several incoherent averaging (compounding) techniques, including spatial, frequency, and temporal compounding.
Spatial compounding during image formation can be accomplished by shifting the transducer in the lateral, axial, or elevational direction. Frequency compounding is performed by dividing the passband of input pulses into several sub-bands in the frequency domain. Temporal compounding produces images by incoherently summing range intensity samples.
These compounding techniques exploit the fact that the ensemble average of a speckle image is the same as the incoherent average of the original object. Since the mottled appearance of speckle noise carries information only about the imaging device and not the imaged object, speckle variations can be reduced by incoherently averaging independent measurements without altering original target contrast. Reduced speckle variation results in improved contrast resolution at the price of reduced detail resolution.
Lipschultz U.S. Pat. No. 5,224,483 discloses a system for enhancing an ultrasound image by reducing clutter in a blood pool area of the image. The blood pool areas are identified by means of low-pass filtering and non-linear intensity mapping, and a mask signal is generated having substantially a first value in areas of tissue and substantially a second value in areas of blood pool. The image signal is then modulated with the mask signal to substantially remove clutter in the blood pool. The mask signal preferably is not strictly binary, but contains some intermediate levels to provide a smooth transition between masked and unmasked regions, so as to prevent an unnatural appearance of the final image. This technique only suppresses clutter in blood pool areas, and does not address the problem of improved contrast resolution in tissue areas.
A need exists for an improved image processor that enhances contrast resolution to improve differentiability of tissue types (liver versus kidney, healthy tissue versus lesion) without losing diagnostically important fine structural details of the image.